{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:TZUIR6NW7YXCNIX3UGXNHULA4R","short_pith_number":"pith:TZUIR6NW","schema_version":"1.0","canonical_sha256":"9e6888f9b6fe2e26a2fba1aed3d160e4770b5e8696267824bca608dadc01dae4","source":{"kind":"arxiv","id":"1107.3600","version":2},"attestation_state":"computed","paper":{"title":"Unsupervised K-Nearest Neighbor Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Oliver Kramer","submitted_at":"2011-07-19T00:48:41Z","abstract_excerpt":"In many scientific disciplines structures in high-dimensional data have to be found, e.g., in stellar spectra, in genome data, or in face recognition tasks. In this work we present a novel approach to non-linear dimensionality reduction. It is based on fitting K-nearest neighbor regression to the unsupervised regression framework for learning of low-dimensional manifolds. Similar to related approaches that are mostly based on kernel methods, unsupervised K-nearest neighbor (UNN) regression optimizes latent variables w.r.t. the data space reconstruction error employing the K-nearest neighbor he"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1107.3600","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-07-19T00:48:41Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"926e4e30711ff7e196613b8ae40092b5c44ffbc3753da2c1bb1ccb9cccf92191","abstract_canon_sha256":"69c3facdbbbe57976f6ec491804d16950d13205cb7da7907b815a1923d6dd575"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:12:20.654255Z","signature_b64":"HRYD1EHId4mxh8ejMHe2ACVODMve8kTImS70G4sbSa+79cLJ6DzODuSD7OMuJqTA7+8wkvwjzDe2GA+W9BzeDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9e6888f9b6fe2e26a2fba1aed3d160e4770b5e8696267824bca608dadc01dae4","last_reissued_at":"2026-05-18T04:12:20.653581Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:12:20.653581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unsupervised K-Nearest Neighbor Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Oliver Kramer","submitted_at":"2011-07-19T00:48:41Z","abstract_excerpt":"In many scientific disciplines structures in high-dimensional data have to be found, e.g., in stellar spectra, in genome data, or in face recognition tasks. In this work we present a novel approach to non-linear dimensionality reduction. It is based on fitting K-nearest neighbor regression to the unsupervised regression framework for learning of low-dimensional manifolds. Similar to related approaches that are mostly based on kernel methods, unsupervised K-nearest neighbor (UNN) regression optimizes latent variables w.r.t. the data space reconstruction error employing the K-nearest neighbor he"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1107.3600","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1107.3600","created_at":"2026-05-18T04:12:20.653666+00:00"},{"alias_kind":"arxiv_version","alias_value":"1107.3600v2","created_at":"2026-05-18T04:12:20.653666+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1107.3600","created_at":"2026-05-18T04:12:20.653666+00:00"},{"alias_kind":"pith_short_12","alias_value":"TZUIR6NW7YXC","created_at":"2026-05-18T12:26:42.757692+00:00"},{"alias_kind":"pith_short_16","alias_value":"TZUIR6NW7YXCNIX3","created_at":"2026-05-18T12:26:42.757692+00:00"},{"alias_kind":"pith_short_8","alias_value":"TZUIR6NW","created_at":"2026-05-18T12:26:42.757692+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R","json":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R.json","graph_json":"https://pith.science/api/pith-number/TZUIR6NW7YXCNIX3UGXNHULA4R/graph.json","events_json":"https://pith.science/api/pith-number/TZUIR6NW7YXCNIX3UGXNHULA4R/events.json","paper":"https://pith.science/paper/TZUIR6NW"},"agent_actions":{"view_html":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R","download_json":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R.json","view_paper":"https://pith.science/paper/TZUIR6NW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1107.3600&json=true","fetch_graph":"https://pith.science/api/pith-number/TZUIR6NW7YXCNIX3UGXNHULA4R/graph.json","fetch_events":"https://pith.science/api/pith-number/TZUIR6NW7YXCNIX3UGXNHULA4R/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R/action/storage_attestation","attest_author":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R/action/author_attestation","sign_citation":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R/action/citation_signature","submit_replication":"https://pith.science/pith/TZUIR6NW7YXCNIX3UGXNHULA4R/action/replication_record"}},"created_at":"2026-05-18T04:12:20.653666+00:00","updated_at":"2026-05-18T04:12:20.653666+00:00"}